357 related articles for article (PubMed ID: 20101242)
1. Prevalent positive epistasis in Escherichia coli and Saccharomyces cerevisiae metabolic networks.
He X; Qian W; Wang Z; Li Y; Zhang J
Nat Genet; 2010 Mar; 42(3):272-6. PubMed ID: 20101242
[TBL] [Abstract][Full Text] [Related]
2. Epistatic interaction maps relative to multiple metabolic phenotypes.
Snitkin ES; Segrè D
PLoS Genet; 2011 Feb; 7(2):e1001294. PubMed ID: 21347328
[TBL] [Abstract][Full Text] [Related]
3. The causes of epistasis in genetic networks.
Macía J; Solé RV; Elena SF
Evolution; 2012 Feb; 66(2):586-96. PubMed ID: 22276550
[TBL] [Abstract][Full Text] [Related]
4. Genetic interaction networks mediate individual statin drug response in
Busby BP; Niktab E; Roberts CA; Sheridan JP; Coorey NV; Senanayake DS; Connor LM; Munkacsi AB; Atkinson PH
NPJ Syst Biol Appl; 2019; 5():35. PubMed ID: 31602312
[TBL] [Abstract][Full Text] [Related]
5. Epistatic interactions among metabolic genes depend upon environmental conditions.
Jagdishchandra Joshi C; Prasad A
Mol Biosyst; 2014 Oct; 10(10):2578-89. PubMed ID: 25018101
[TBL] [Abstract][Full Text] [Related]
6. Variance in epistasis links gene regulation and evolutionary rate in the yeast genetic interaction network.
Fierst JL; Phillips PC
Genome Biol Evol; 2012; 4(11):1080-7. PubMed ID: 23019067
[TBL] [Abstract][Full Text] [Related]
7. Plasticity and epistasis strongly affect bacterial fitness after losing multiple metabolic genes.
D'Souza G; Waschina S; Kaleta C; Kost C
Evolution; 2015 May; 69(5):1244-54. PubMed ID: 25765095
[TBL] [Abstract][Full Text] [Related]
8. Identification of response-modulated genetic interactions by sensitivity-based epistatic analysis.
Batenchuk C; Tepliakova L; Kaern M
BMC Genomics; 2010 Sep; 11():493. PubMed ID: 20831804
[TBL] [Abstract][Full Text] [Related]
9. Imputing and predicting quantitative genetic interactions in epistatic MAPs.
Ryan C; Cagney G; Krogan N; Cunningham P; Greene D
Methods Mol Biol; 2011; 781():353-61. PubMed ID: 21877290
[TBL] [Abstract][Full Text] [Related]
10. Quantitative genetic analysis in Saccharomyces cerevisiae using epistatic miniarray profiles (E-MAPs) and its application to chromatin functions.
Schuldiner M; Collins SR; Weissman JS; Krogan NJ
Methods; 2006 Dec; 40(4):344-52. PubMed ID: 17101447
[TBL] [Abstract][Full Text] [Related]
11. The Saccharomyces cerevisiae RAD30 gene, a homologue of Escherichia coli dinB and umuC, is DNA damage inducible and functions in a novel error-free postreplication repair mechanism.
McDonald JP; Levine AS; Woodgate R
Genetics; 1997 Dec; 147(4):1557-68. PubMed ID: 9409821
[TBL] [Abstract][Full Text] [Related]
12. Comparative analysis of the transcription-factor gene regulatory networks of E. coli and S. cerevisiae.
Guzmán-Vargas L; Santillán M
BMC Syst Biol; 2008 Jan; 2():13. PubMed ID: 18237429
[TBL] [Abstract][Full Text] [Related]
13. An integrated approach to characterize genetic interaction networks in yeast metabolism.
Szappanos B; Kovács K; Szamecz B; Honti F; Costanzo M; Baryshnikova A; Gelius-Dietrich G; Lercher MJ; Jelasity M; Myers CL; Andrews BJ; Boone C; Oliver SG; Pál C; Papp B
Nat Genet; 2011 May; 43(7):656-62. PubMed ID: 21623372
[TBL] [Abstract][Full Text] [Related]
14. Dynamic epistasis under varying environmental perturbations.
Barker B; Xu L; Gu Z
PLoS One; 2015; 10(1):e0114911. PubMed ID: 25625594
[TBL] [Abstract][Full Text] [Related]
15. Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.
Sato TK; Tremaine M; Parreiras LS; Hebert AS; Myers KS; Higbee AJ; Sardi M; McIlwain SJ; Ong IM; Breuer RJ; Avanasi Narasimhan R; McGee MA; Dickinson Q; La Reau A; Xie D; Tian M; Reed JL; Zhang Y; Coon JJ; Hittinger CT; Gasch AP; Landick R
PLoS Genet; 2016 Oct; 12(10):e1006372. PubMed ID: 27741250
[TBL] [Abstract][Full Text] [Related]
16. Semi-supervised prediction of gene regulatory networks using machine learning algorithms.
Patel N; Wang JT
J Biosci; 2015 Oct; 40(4):731-40. PubMed ID: 26564975
[TBL] [Abstract][Full Text] [Related]
17. Interpreting patterns of gene expression: signatures of coregulation, the data processing inequality, and triplet motifs.
Ku WL; Duggal G; Li Y; Girvan M; Ott E
PLoS One; 2012; 7(2):e31969. PubMed ID: 22393375
[TBL] [Abstract][Full Text] [Related]
18. HiNO: an approach for inferring hierarchical organization from regulatory networks.
Hartsperger ML; Strache R; Stümpflen V
PLoS One; 2010 Nov; 5(11):e13698. PubMed ID: 21079808
[TBL] [Abstract][Full Text] [Related]
19. Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets.
Lu X; Kensche PR; Huynen MA; Notebaart RA
Nat Commun; 2013; 4():2124. PubMed ID: 23851603
[TBL] [Abstract][Full Text] [Related]
20. A global genetic interaction network maps a wiring diagram of cellular function.
Costanzo M; VanderSluis B; Koch EN; Baryshnikova A; Pons C; Tan G; Wang W; Usaj M; Hanchard J; Lee SD; Pelechano V; Styles EB; Billmann M; van Leeuwen J; van Dyk N; Lin ZY; Kuzmin E; Nelson J; Piotrowski JS; Srikumar T; Bahr S; Chen Y; Deshpande R; Kurat CF; Li SC; Li Z; Usaj MM; Okada H; Pascoe N; San Luis BJ; Sharifpoor S; Shuteriqi E; Simpkins SW; Snider J; Suresh HG; Tan Y; Zhu H; Malod-Dognin N; Janjic V; Przulj N; Troyanskaya OG; Stagljar I; Xia T; Ohya Y; Gingras AC; Raught B; Boutros M; Steinmetz LM; Moore CL; Rosebrock AP; Caudy AA; Myers CL; Andrews B; Boone C
Science; 2016 Sep; 353(6306):. PubMed ID: 27708008
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
